T-SNE is a machine learning algorithm for data visualization (usually), which is based on a nonlinear dimensionality reduction technique.

The basic idea of t-SNE is to reduce dimensional space keeping relative pairwise distance between points. In other words, the algorithm maps multi-dimensional data to two or more dimensions, where points which were initially far from each other are also located far away, and close points are also converted to close ones.

It can be said that t-SNE looking for a new data representation where the neighborhood relations are preserved.