diff --git a/doc/whats_new/v1.6.rst b/doc/whats_new/v1.6.rst
index 065be410a6273..2eb61d3875859 100644
--- a/doc/whats_new/v1.6.rst
+++ b/doc/whats_new/v1.6.rst
@@ -56,6 +56,12 @@ See :ref:`array_api` for more details.
   compatible inputs when their base estimators do. :pr:`27096` by :user:`Tim
   Head <betatim>` and :user:`Olivier Grisel <ogrisel>`.
 
+Other changes impacting array API support in general:
+
+- |Fix| func:`validation.check_array` now accepts scipy sparse inputs without error
+  even when array API dispatch is enabled.
+  :pr:`29466` by :user:`Olivier Grisel <ogrisel>`.
+
 Metadata Routing
 ----------------
 
diff --git a/sklearn/utils/_array_api.py b/sklearn/utils/_array_api.py
index a00d250ab31d2..5d172a021233f 100644
--- a/sklearn/utils/_array_api.py
+++ b/sklearn/utils/_array_api.py
@@ -5,6 +5,7 @@
 from functools import wraps
 
 import numpy
+import scipy.sparse as sp
 import scipy.special as special
 
 from .._config import get_config
@@ -550,6 +551,19 @@ def get_namespace(*arrays, remove_none=True, remove_types=(str,), xp=None):
     # message in case it is missing.
     import array_api_compat
 
+    # Special handling of scipy sparse inputs, potentially mixed with dense
+    # arrays.
+    if all(sp.issparse(a) for a in arrays):
+        # For all-scipy sparse inputs, it's safe to assume that the namespace
+        # is numpy (or its array-api-compat wrapper for versions before 2.0).
+        return array_api_compat.get_namespace(numpy.empty(shape=0)), True
+    else:
+        # For mixed dense/sparse array inputs, ignore the sparse arrays and
+        # proceed only with the dense ones. The caller code in scikit-learn
+        # should always be in charge of special handling scipy sparse
+        # operations under sp.issparse() branches when needed.
+        arrays = [a for a in arrays if not sp.issparse(a)]
+
     namespace, is_array_api_compliant = array_api_compat.get_namespace(*arrays), True
 
     # These namespaces need additional wrapping to smooth out small differences
diff --git a/sklearn/utils/tests/test_array_api.py b/sklearn/utils/tests/test_array_api.py
index 71f499f7a8dae..e3695b17c5268 100644
--- a/sklearn/utils/tests/test_array_api.py
+++ b/sklearn/utils/tests/test_array_api.py
@@ -3,6 +3,7 @@
 
 import numpy
 import pytest
+import scipy.sparse as sp
 from numpy.testing import assert_allclose
 
 from sklearn._config import config_context
@@ -60,19 +61,31 @@ def test_get_namespace_ndarray_creation_device():
 @skip_if_array_api_compat_not_configured
 def test_get_namespace_ndarray_with_dispatch():
     """Test get_namespace on NumPy ndarrays."""
-    array_api_compat = pytest.importorskip("array_api_compat")
+    array_api_compat_numpy = pytest.importorskip("array_api_compat.numpy")
 
     X_np = numpy.asarray([[1, 2, 3]])
+    if np_version >= parse_version("2.0.0"):
+        # NumPy 2.0+ is an array API compliant library.
+        expected_namespace = numpy
+    else:
+        # Older NumPy versions require the compatibility layer.
+        expected_namespace = array_api_compat_numpy
 
     with config_context(array_api_dispatch=True):
         xp_out, is_array_api_compliant = get_namespace(X_np)
         assert is_array_api_compliant
-        if np_version >= parse_version("2.0.0"):
-            # NumPy 2.0+ is an array API compliant library.
-            assert xp_out is numpy
-        else:
-            # Older NumPy versions require the compatibility layer.
-            assert xp_out is array_api_compat.numpy
+        assert xp_out is expected_namespace
+
+    X_sp = sp.csr_array(X_np)
+    with config_context(array_api_dispatch=True):
+        xp_out, is_array_api_compliant = get_namespace(X_sp)
+        assert is_array_api_compliant
+        assert xp_out is expected_namespace
+
+    with config_context(array_api_dispatch=True):
+        xp_out, is_array_api_compliant = get_namespace(X_np, X_sp)
+        assert is_array_api_compliant
+        assert xp_out is expected_namespace
 
 
 @skip_if_array_api_compat_not_configured
@@ -82,13 +95,20 @@ def test_get_namespace_array_api():
 
     X_np = numpy.asarray([[1, 2, 3]])
     X_xp = xp.asarray(X_np)
+    X_sp = sp.csr_array(X_np)
+
     with config_context(array_api_dispatch=True):
         xp_out, is_array_api_compliant = get_namespace(X_xp)
         assert is_array_api_compliant
+        assert xp_out is xp
 
         with pytest.raises(TypeError):
             xp_out, is_array_api_compliant = get_namespace(X_xp, X_np)
 
+        xp_out, is_array_api_compliant = get_namespace(X_xp, X_sp)
+        assert is_array_api_compliant
+        assert xp_out is xp
+
 
 class _AdjustableNameAPITestWrapper(_ArrayAPIWrapper):
     """API wrapper that has an adjustable name. Used for testing."""
diff --git a/sklearn/utils/tests/test_validation.py b/sklearn/utils/tests/test_validation.py
index 5bde51ae514d9..afc3d743a95d6 100644
--- a/sklearn/utils/tests/test_validation.py
+++ b/sklearn/utils/tests/test_validation.py
@@ -2018,6 +2018,16 @@ def test_check_array_array_api_has_non_finite(array_namespace):
             check_array(X_inf)
 
 
+@skip_if_array_api_compat_not_configured
+def test_check_array_on_sparse_inputs_with_array_api_enabled():
+    X_sp = sp.csr_array([[0, 1, 0], [1, 0, 1]])
+    with config_context(array_api_dispatch=True):
+        assert sp.issparse(check_array(X_sp, accept_sparse=True))
+
+        with pytest.raises(TypeError):
+            check_array(X_sp)
+
+
 @pytest.mark.parametrize(
     "extension_dtype, regular_dtype",
     [