Overfitting a model means creating a model which produces a prediction based on the observations of a sample too small.
Example: You've visited London for a weekend and the weather was perfectly sunny. You come back home telling your friends that London is ALWAYS sunny...based on the observations of 2 days out of 365 days. We know it's not true, no offense :)
Now that you have the idea, it would be the same as building a model based on Sales feedback that two 30-people Gaming companies from Iceland converted in the last month out of the 3 leads received from this market, and therefore these should be your most highly scored Leads.
To avoid overfitting the model, we avoid having trees too deep, making sure all the end nodes have a minimum population of ~ 100 leads.