No this is quite a bit different. In transfer learning in computer vision, people are using a network trained on another, typically large dataset, and using the learned features on a different data set.

This LSTM simply learned to predict the data. It didn't learn some other supervised task.

This would be more similar to autoencoder pretraining, but even that is not quite the same.