From the 5 assignments of values to a, b and c in the training set, out of the 8 possible assignments, the decision tree makes predictions in all 8 cases. The ability to make predictions in unseen cases is the bias of the learning algorithm. The unseen cases are:
The bias is that c is always irrelevant to the classification, and that when a is true, b is also irrelevant. This is because c always seemed to be irrelevant in the training example. Similarly b was irrelevant when a was true.
a b c prediction for d true true true false true false true false false false false false