I know that this involves probability but I don't get what is it asking

Five different models are fit using the same training data set, and the tested on the same (separate) test set (which has the same size as the training set). The root mean square (RMS) prediction errors for each model, on the training and test sets, are reported below. Comment on the results for each model. You might mention whether the model's predictions are good or bad, whether it is likely to generalize to unseen data, or whether it is over-fit. You are also welcome to say that you don't believe the results, or think the reported numbers are fishy. Model Train RMS Test RMS A 1.355 1.423 B 5.033 0.889 C 0.633 0.633 D 9.760 9.165 ET E 0.211 5.072