What is leakage in frequency domain adaptive filters?
In adaptive filtering, leakage is a stabilization method which may be useful if the covariance matrix is close to singular (i.e. at least one of the eigenvalues is very small), or if there are finite-precision effects in the implementation of the adaptive filter. Leakage changes the update formula such that not only the mean squared error but also the norm of the filter taps is minimized. This prevents unbounded growth of the filter coefficients in cases of numerical ill-conditioning.

For you this simply means that you initially use a leakage factor of 1 (i.e. no leakage) if the FDAF works properly with your input signals. If you encounter coefficient drift (large fluctuation about the optimum solution), you can start by slightly decreasing the leakage factor until the coefficient fluctuation becomes sufficiently small. Note that leakage achieves stabilization at the expense of performance degradation because due to the changed update formula it introduces some bias in the filter taps.