What does overfitting in a machine learning model mean?

A$.$

The model$$s predictions are always $100\%$ accurate.

B$.$

The model requires too much data to train effectively.

C$.$

The model performs well on the training data but poorly on unseen data.

D$.$

The model is too simple to capture the underlying trend of the data.