The inductive bias of a learning algorithm is the set of assumptions that the learner uses to predict outputs given inputs that it has not encountered—Tom Mitchell
"Inductive bias" refers to your suspicion that if the sun has risen for the last billion days in a row, then it may rise tomorrow as well. Since it is logically possible that the laws of physics will arbitrarily cease to work and that the sun will *not* rise tomorrow, coming to this conclusion requires an inductively biased prior.
This sort of bias is not a bad thing - without "inductive bias" you can't draw any conclusion at all from the data. It's just a different technical meaning attached to the same word.
- Tom M. Mitchell (1980) (PDF). The need for biases in learning generalizations. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.120.4179.