  In this paper we obtain non-uniform exponential upper bounds for the rate of
convergence of a version of the algorithm Context, when the underlying tree is
not necessarily bounded. The algorithm Context is a well-known tool to estimate
the context tree of a Variable Length Markov Chain. As a consequence of the
exponential bounds we obtain a strong consistency result. We generalize in this
way several previous results in the field.
