I would like to see others who might be more expert in qualitative research address this, and I will eagerly read the answers. But to start the ball rolling, for me, as qualitative research does not, in general, set inference as a goal, estimation of sample size for the purpose of generalization to a population, known or unknown, seems irrelevant. That is, the sample size needed would be judged on other grounds, perhaps estimated likelihood of answer saturation.

Umar M. Modibbo You may check this paper that proposed some new ideas Article A Frequentist Alternative to Significance Testing, p-Values,...

Determination of the sample size in known or unknown populations in qualitative research may decide based on the quality of data (how data saturation can achieve) not the number of informants.

According to Saunders et al. (2012), number of informants may vary between 5 - 25 in a qualitative study. Also, theoretical sampling is much important as we recruit informants based on their expertise, knowledge, and experience.

Rather than a specific recommendation for N, what I would like to see considered is the distinctly different goals of qualitative methods in respect to what are traditionally considered "quantitative" methods. What is typically intended by quantitative methods are inferential statistical methods (there are other quantitative methods, but that is beyond the scope of this argument). The key for me, and I welcome argument herein, is that inference is not a goal of qualitative research; instead deep penetration with the sample at hand is the objective. Thus, the notion of "saturation" that I and Roshan Nimantha Panditharathna mentioned is often used in thinking about how many, but even of more importance WHO, is sampled in a qualitative study. Thus the use of inferential notions to guide in consideration of sample size is an inappropriate conflation of methods.