(C) Statement 1 is correct but Statement 2 is incorrect.
Statement 1 is correct as overfitting means the model memorizes training data. Statement 2 is incorrect because using the same data for training and evaluation leads to overfitting, not accurate results.
The source passage explicitly states: "It's not recommended to use the data we used to build the model to evaluate it… the model will simply remember the whole training set… This is known as overfitting." So Statement 2 is clearly wrong. Statement 1 matches the textbook definition of overfitting directly.