diff --git a/modAL/models/learners.py b/modAL/models/learners.py
index 7fdcf2c..b4ea394 100644
--- a/modAL/models/learners.py
+++ b/modAL/models/learners.py
@@ -311,6 +311,20 @@ def _set_classes(self):
 
     def _add_training_data(self, X: modALinput, y: modALinput):
         super()._add_training_data(X, y)
+
+    def teach(self, X: modALinput, y: modALinput, bootstrap: bool = False, only_new: bool = False, **fit_kwargs) -> None:
+        """
+        Adds X and y to the known training data for each learner and retrains learners with the augmented dataset.
+
+        Args:
+            X: The new samples for which the labels are supplied by the expert.
+            y: Labels corresponding to the new instances in X.
+            bootstrap: If True, trains each learner on a bootstrapped set. Useful when building the ensemble by bagging.
+            only_new: If True, the model is retrained using only X and y, ignoring the previously provided examples.
+            **fit_kwargs: Keyword arguments to be passed to the fit method of the predictor.
+        """
+
+        super().teach(X, y, bootstrap=bootstrap, only_new=only_new, **fit_kwargs)
         self._set_classes()
 
     def predict(self, X: modALinput, **predict_proba_kwargs) -> Any: