Well, if we want to do linear regression with, say 5 pairs, we'll get a certain model. But if three of the elements are missing, we only have to fit the model to two points. Naturally, this will give a perfect fitting model. Hence, fitting to fewer data is easier statistically (not numerically; it usually takes longer). However, better fit does not necessarily mean a better model.