What does "Norm" term mean?
A norm is a concept in linear algebra which assigns a size to a vector. Many different norms exist you can read up on their many uses here. 

In this paper, they are training a recurrent neural network. These are used for time series data. The assumption is a hidden state should be similar for successive time inputs $t$ and $t-1$. Thus, the author proposes an additional constraint based on the relative size of the successive hidden state vectors as

$||h_{t}||_2 - ||h_{t-1}||_2$.

The more different the norm of these successive states, the greater the cost will be.