Why does a machine learning algorithm need a bias?
Inductive bias means all assumptions your learning approach assumes for generalising to unseen data. What we do in machine learning is induction which means we don't have rules. By seeing data, we make rules. For example, in linear regression you may consider that the output is linear with respect to inputs, or it is polynomial. Another example can be this that in women gesture recognition, you don't care about moustaches because you know they do not have that. You can also take a look at here.