This paper investigates the application of genetic algorithms to the decoding problem of error-correcting codes. The basic operations of crossover, mutation and selection are appropriately defined for the decoding problem of binary linear block codes without the knowledge of any algebraic structure. Simulation results indicate that these evolutionary techniques, if properly applied, can provide very interesting results for this difficult combinatorial problem. The result were obtained for hard-decision decoding of binary linear block codes, but the algorithms can be generalized to soft-decision decoding and to other kinds of linear codes. The algorithms presented are in fact evolutionary versions of the well known information set decoding.