# what does the correlation of Random forest regression tool in R represent

I've built a random forest model (regression model) using randomForest package in R, and I calculate the correlation between the predicted values and the actual ones in order to know how the trained model is going to perform, which is very high in my case, so I was wondering in such case how this correlation is build, I mean is it leave one out correlation or any type of cross validation correlation or just random and can't represent the real performance of the model when tested on unseen new cases???? the following is a snapshot of my script for calculating the correlation where x is the data (observations) and y is the numeric values I want the model to learn/predict (in the testing cases):

mytr_all = randomForest(x, y, ntree = 500,corr.bias=TRUE)
cor(mytr_all$y,mytr_all$predicted)