What does overfitting indicate?

Correct answer: The model learns the specific details or noise in the training data too closely

Overfitting occurs when a model learns the training data, including its specific details or noise, too closely. It may achieve very good training performance but perform poorly on unseen data. Option B describes good generalization, while option C more closely describes underfitting.