The Baldwin effect is known as an interaction between learning and evolution, which suggests that individual lifetime learning can influence the course of evolution without the Lamarckian mechanism. Since Hinton and Nowlan showed this by computer simulation, many studies have been conducted in the static environment. Our concern is to consider the Baldwin effect in dynamic environment, especially when there is no explicit optimal solution through generations and it only depends on interactions among agents. We adopt the iterated Prisoner's Dilemma as a dynamic environment and introduce phenotypic plasticity to strategies by using a meta-learning rule termed "Meta-Pavlov". In this simulation, the Baldwin effect was observed as follows : First, strategies with enough plasticity spread, which caused a shift from defective population to cooperative. Second, these strategies were replaced by the strategy [x00x] which has a modest amount of plasticity. We have analyzed this strategy and have shown that it satisfies the ESS (Evolutionarily Stable Strategy) condition and establishes robust and cooperative relationships in the population.