Random Forests can overfit, but with sufficient data (and no data leakage) it is difficult to do so.

The final output of a random forest regression for example is just the average of all the final prediction nodes of the individual trees, which thanks to bootstrapping are decorrelated. So - adding more trees does not tend to alter predictions very much.