Overfitting occurs when an AI model becomes too specialized in the training data and performs poorly on new, unseen data. This happens when the model learns the noise or irrelevant patterns present in the training dataset, instead of generalizing the underlying patterns. To address overfitting, techniques like regularization and early stopping can be employed during the training process.