You have an example of a bias estimator that's consistent right here.

Constistency usually refers to convergence in probability (MOO)

Some people talk about strong (almost sure) consistency

and weak constistency (convergence in probability).

But most just say an estimator is consistent if it converges in probability to the parameter it's estimating.

That's consistent with Wackerly (pun intented).