# Why is large decision tree likely to overfit

My lecture slide told me that if we don't prune the regression tree, then the tree likely to over-fit. So, I wonder why would that happen? Is that because if the tree grows too large, we would end up with very little instances on each leaf nodes of the tree so the estimated mean value on each leaf node will be not accurate?