Explanation of inductive bias of Candidate Elimination Algorithm

The definition of inductive bias says that

The inductive bias (also known as learning bias) of a learning algorithm is the set of assumptions that the learner uses to predict outputs given inputs that it has not encountered.

The inductive bias of Candidate elimination says that

The target concept c is contained in the given hypothesis space H

My question is , how does this inductive bias help us to predict for next instance in given dataset?