Overfitting is "the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit additional data or predict future observations reliably".
An Overfitted Model is a statistical model that contains more parameters than can be justified by the data. Here, to evaluate the AI model it is not necessary to use the data that is used to build the model. Because AI Model remembers the whole training data set, therefore it always predicts the correct label for any point in the training dataset. This is known as Overfitting
Models that use the training dataset during testing, will always results in correct output. This is known as overfitting.