How to determine number of leaves in decision tree analysis?
I'll assume that your test and validation datasets have been created appropriately (e.g. no observations are in both test and validation sets, both sets are of appropriate size, etc.).

Overfitting means that your model fits very well to your training data but does not generalise well on unseen data (i.e. will perform poorly on your validation dataset).

Your misclassification rate on the validation set (unseen data) is decreasing, and is therefore a good thing. However, if the misclassification rate on the validation set were to increase, that would indicate overfitting.