Question about scaling learning rate in source code

I was trying to better understand some of the internals of XGBoost, and I saw that in the source code, when a tree is grown, the learning rate is scaled by the number of trees, at that iteration.
I was curious why this is? And so this means, as the number of estimators increases, the learning rate used gets smaller?
See the source code bellow, I also see this in all of the updater classes.