diff --git a/sklearn/gaussian_process/_gpc.py b/sklearn/gaussian_process/_gpc.py
index 2c9c0ef483d4f..9f6ed460c4ad5 100644
--- a/sklearn/gaussian_process/_gpc.py
+++ b/sklearn/gaussian_process/_gpc.py
@@ -555,6 +555,10 @@ def optimizer(obj_func, initial_theta, bounds):
 
     Attributes
     ----------
+    base_estimator_ : ``Estimator`` instance
+        The estimator instance that defines the likelihood function
+        using the observed data.
+
     kernel_ : kernel instance
         The kernel used for prediction. In case of binary classification,
         the structure of the kernel is the same as the one passed as parameter
diff --git a/sklearn/tests/test_docstring_parameters.py b/sklearn/tests/test_docstring_parameters.py
index 6d79149ca0832..4f2c43f61d97f 100644
--- a/sklearn/tests/test_docstring_parameters.py
+++ b/sklearn/tests/test_docstring_parameters.py
@@ -229,7 +229,7 @@ def test_fit_docstring_attributes(name, Estimator):
             assert hasattr(est, attr.name)
 
     IGNORED = {'BayesianRidge', 'Birch', 'CCA', 'CategoricalNB', 'ElasticNet',
-               'ElasticNetCV', 'GaussianProcessClassifier',
+               'ElasticNetCV',
                'HistGradientBoostingClassifier',
                'HistGradientBoostingRegressor',
                'KernelCenterer', 'KernelDensity',