The main reason why RNNs are suitable for sequence problems is that:

There are two sets of weight matrices WF and WR$,$ which increases the $$learning capacity$$ of the network.

The state of the network updates itself as it sees new elements in the sequence.

They can take sequences as inputs which normal neural networks cannot do$.$