When applying deep learning to real-world data, how should Overfitting be understood? Focus on the most precise definition.

A. Overfitting always improves test accuracy B. Overfitting occurs only in linear regression C. Overfitting occurs when a model learns noise or specific training patterns too strongly D. Overfitting means the model is too simple for the data