This paper is concerned with nonlinear filtering and control of a switching diffusion coupled by an unknown Markov chain. Two statistical estimation methods are used to track the unknown Markov chain. Computable approximate filters are obtained based on these methods. The filters are then used to construct controls for the partially observed system. These controls are shown to be asymptotically optimal as the observation noise tends to zero. Finally an example is considered and numerical experiments are reported.