Convergence is a term that describes the situation where an algorithm computes iteratively a solution, and the results are, after a while, closer and closer.
Your quote seems to refer to genetic algorithms. These are driven by randomness, and start each time with very different results. But a fitness function makes sure to optimise the solution from one iteration to the other. If the fitness function is well designed, you then end up with a smaller and smaller set of changes in the result set.
The speed of convergence is in this regard well defined (the only ambiguity, is whether it's mesured according to the time or the number of iteration). Example (wikipedia):
For specific optimization problems and problem instances, other optimization algorithms may be more efficient than genetic algorithms in terms of speed of convergence.
Another term that is more frequently used is the rate of convergence.
Not related: No problem with convergence and speed. But I'd suggest to have a second thought at "for the individuals in the population to get closer...". This might mislead to think that the individuals evolve to get closer. However, I leave it up to you since we would slip into subjective wording issues