diff --git a/sklearn/datasets/_samples_generator.py b/sklearn/datasets/_samples_generator.py
index 9a972ba031bd3..a3495b358354f 100644
--- a/sklearn/datasets/_samples_generator.py
+++ b/sklearn/datasets/_samples_generator.py
@@ -672,6 +672,15 @@ def make_regression(
         return X, y
 
 
+@validate_params(
+    {
+        "n_samples": [Interval(Integral, 0, None, closed="left"), tuple],
+        "shuffle": ["boolean"],
+        "noise": [Interval(Real, 0, None, closed="left"), None],
+        "random_state": ["random_state"],
+        "factor": [Interval(Real, 0, 1, closed="left")],
+    }
+)
 def make_circles(
     n_samples=100, *, shuffle=True, noise=None, random_state=None, factor=0.8
 ):
@@ -706,7 +715,7 @@ def make_circles(
         See :term:`Glossary <random_state>`.
 
     factor : float, default=.8
-        Scale factor between inner and outer circle in the range `(0, 1)`.
+        Scale factor between inner and outer circle in the range `[0, 1)`.
 
     Returns
     -------
@@ -716,20 +725,13 @@ def make_circles(
     y : ndarray of shape (n_samples,)
         The integer labels (0 or 1) for class membership of each sample.
     """
-
-    if factor >= 1 or factor < 0:
-        raise ValueError("'factor' has to be between 0 and 1.")
-
     if isinstance(n_samples, numbers.Integral):
         n_samples_out = n_samples // 2
         n_samples_in = n_samples - n_samples_out
-    else:
-        try:
-            n_samples_out, n_samples_in = n_samples
-        except ValueError as e:
-            raise ValueError(
-                "`n_samples` can be either an int or a two-element tuple."
-            ) from e
+    else:  # n_samples is a tuple
+        if len(n_samples) != 2:
+            raise ValueError("When a tuple, n_samples must have exactly two elements.")
+        n_samples_out, n_samples_in = n_samples
 
     generator = check_random_state(random_state)
     # so as not to have the first point = last point, we set endpoint=False
diff --git a/sklearn/datasets/tests/test_samples_generator.py b/sklearn/datasets/tests/test_samples_generator.py
index 09c245667c0a3..13df2bc796a55 100644
--- a/sklearn/datasets/tests/test_samples_generator.py
+++ b/sklearn/datasets/tests/test_samples_generator.py
@@ -688,11 +688,6 @@ def test_make_circles():
             2,
         ), "Samples not correctly distributed across circles."
 
-    with pytest.raises(ValueError):
-        make_circles(factor=-0.01)
-    with pytest.raises(ValueError):
-        make_circles(factor=1.0)
-
 
 def test_make_circles_unbalanced():
     X, y = make_circles(n_samples=(2, 8))
@@ -704,12 +699,6 @@ def test_make_circles_unbalanced():
 
     with pytest.raises(
         ValueError,
-        match=r"`n_samples` can be either an int " r"or a two-element tuple.",
-    ):
-        make_circles(n_samples=[1, 2, 3])
-
-    with pytest.raises(
-        ValueError,
-        match=r"`n_samples` can be either an int " r"or a two-element tuple.",
+        match="When a tuple, n_samples must have exactly two elements.",
     ):
         make_circles(n_samples=(10,))
diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py
index 31aeb37c5e536..c89ce2481bd61 100644
--- a/sklearn/tests/test_public_functions.py
+++ b/sklearn/tests/test_public_functions.py
@@ -111,6 +111,7 @@ def _check_function_param_validation(
     "sklearn.datasets.fetch_olivetti_faces",
     "sklearn.datasets.load_svmlight_file",
     "sklearn.datasets.load_svmlight_files",
+    "sklearn.datasets.make_circles",
     "sklearn.datasets.make_classification",
     "sklearn.datasets.make_friedman1",
     "sklearn.datasets.make_sparse_coded_signal",