What is "lag" in time series forecasting?
Lag features are target values from previous periods. 

For example, if you would like to forecast the sales of a retail outlet in period $t$ you can use the sales of the previous month $t-1$ as a feature. That would be a lag of 1 and you could say it models some kind of momentum. But you could also apply a lag of 12 to model the sales of the same month a year ago (since retail sales are often seasonal depending on the format, category and SKU). Accordingly, it depends on the dataset which lags work best and looking at correlation is one way to select the lag values. 

Have a look at this blog post for a simple explanation of lag features.