diff --git a/sklearn/metrics/_ranking.py b/sklearn/metrics/_ranking.py
index 7ec583177328c..4b8202d60d53e 100644
--- a/sklearn/metrics/_ranking.py
+++ b/sklearn/metrics/_ranking.py
@@ -1165,6 +1165,13 @@ def label_ranking_average_precision_score(y_true, y_score, *, sample_weight=None
     return out
 
 
+@validate_params(
+    {
+        "y_true": ["array-like"],
+        "y_score": ["array-like"],
+        "sample_weight": ["array-like", None],
+    }
+)
 def coverage_error(y_true, y_score, *, sample_weight=None):
     """Coverage error measure.
 
@@ -1183,10 +1190,10 @@ def coverage_error(y_true, y_score, *, sample_weight=None):
 
     Parameters
     ----------
-    y_true : ndarray of shape (n_samples, n_labels)
+    y_true : array-like of shape (n_samples, n_labels)
         True binary labels in binary indicator format.
 
-    y_score : ndarray of shape (n_samples, n_labels)
+    y_score : array-like of shape (n_samples, n_labels)
         Target scores, can either be probability estimates of the positive
         class, confidence values, or non-thresholded measure of decisions
         (as returned by "decision_function" on some classifiers).
diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py
index 8729ce1f0869e..836139b85b341 100644
--- a/sklearn/tests/test_public_functions.py
+++ b/sklearn/tests/test_public_functions.py
@@ -122,6 +122,7 @@ def _check_function_param_validation(
     "sklearn.metrics.cluster.contingency_matrix",
     "sklearn.metrics.cohen_kappa_score",
     "sklearn.metrics.confusion_matrix",
+    "sklearn.metrics.coverage_error",
     "sklearn.metrics.d2_pinball_score",
     "sklearn.metrics.det_curve",
     "sklearn.metrics.f1_score",