Dealing with little available data: transfer learning

Suppose I seek to predict a certain numerical value, whereby the data set which contains the predetermined correct labels is only very small. However, I'm also provided a large data set with a label that is correlated to the one I want to predict. I read that transfer learning could be used to make use of this larger data set for predicting the desired label from the smaller data set. Could someone elaborate a bit on this?