In most NLP problems, the data is present in structured forms, like strings or trees, and this structural information can be effectively passed to a kernel-based learning algorithm using an appropriate kernel, like a string kernel (Lodhi et al., 2002) or a tree kernel (Collins and Duffy, 2001).
feature-based methods require reducing the data to a pre-defined set of features often leading to some loss of the useful structural information present in the data.